Senior Staff Software Engineer - Data Platform - Kubernetes - Distributed Systems - Federal

ServiceNow•Santa Clara, CA

30d•$149,800 - $262,200•Hybrid

About The Position

ServiceNow is seeking a Senior Staff Software Engineer (IC5) for its Data Platform Engineering organization. This hands-on technical lead will design and deliver shared, multi-tenant platform services—including managed Postgres, queueing and streaming, and key-value/cache services—running on Kubernetes across a large global fleet. The role owns these services from design through production operations and serves as a technical anchor for their availability, resilience, and operating model. The position supports US Regulated Markets and is flexible hybrid, requiring two days per week in a ServiceNow office. Candidates must pass the USFedPASS background screening, including credit and criminal/misdemeanor checks and a drug test; only US citizens, naturalized citizens, or US permanent residents holding a green card will be considered. The engineer will lead major technical initiatives, turn ambiguous platform challenges into executable designs with explicit availability, durability, and cost targets, and define high-availability, failover, disaster-recovery, and multi-region architectures. They will develop Kubernetes-native automation such as operators, controllers, CRDs, and self-service APIs to provision, scale, upgrade, and fail over services without human intervention. The role partners with principal and distinguished engineers on platform architecture and standards, and with product teams on consumption contracts, tenancy models, and SLOs. The position emphasizes reliability, scalability, and operability, including early identification and resolution of technical risks, failure-mode analysis, game days, and post-incident reviews. The engineer will spend significant time designing, coding, and reviewing core systems, and will mentor mid-level and junior engineers through code reviews, design feedback, and pairing, particularly in distributed systems and data-service design. Candidates should also be able to think critically about integrating AI into engineering and platform work.

Requirements

Experience leveraging or critically thinking about integrating AI into engineering and platform work, such as AI-powered tooling, operational workflow automation, agentic systems for fleet visibility and operations, or AI's impact on infrastructure.
12+ years of software development experience with a Bachelor's degree; or 8+ years with a Master's degree; or 5+ years with a PhD; or equivalent work experience.
8+ years building production software, with solid experience operating distributed systems and running stateful workloads on Kubernetes at scale.
Track record of leading the design and delivery of at least one broadly used shared, multi-tenant infrastructure service, such as a relational database, message queue or streaming platform, or key-value/cache service, including its high availability, failover, and operating model.
Deep understanding of high availability and failure handling, including replication topologies, leader election, quorum and consensus, split-brain avoidance, backup and restore, point-in-time recovery, and explicit RPO/RTO and durability targets.
Strong system-design skills, including consistency models, partitioning and rebalancing, capacity planning, tenant isolation, and noisy-neighbor mitigation, with ability to communicate trade-offs clearly.
Hands-on experience with at least one major hyperscaler (AWS, Azure, or GCP), including core compute, networking, storage, and IAM primitives.
Strong working knowledge of containers and Kubernetes, including StatefulSets, CSI/persistent storage, PDBs, and topology spread; CI/CD and GitOps-based delivery; and infrastructure as code.
Strong programming skills in Go, or strong systems-language skills and willingness to work primarily in Go.
Must pass the ServiceNow USFedPASS screening, including a credit check, criminal/misdemeanor check, and drug test.
Must be a US citizen, naturalized US citizen, or US permanent resident holding a green card.

Nice To Haves

Experience building or extending Kubernetes operators for stateful systems, such as CloudNativePG, Zalando/Crunchy Postgres operators, Strimzi, or Redis/Valkey operators, and judgment about when to adopt versus build.
Deep expertise in one target system: Postgres internals; Kafka/NATS; or Redis/Valkey.
Experience running data services across multiple regions or clusters, including cross-region replication, failover orchestration, and disaster-recovery testing.
Experience with zero-downtime upgrades, schema/data migrations, and fleet-wide rollouts of stateful services.
Experience with observability and SLOs for stateful systems, including replication lag, saturation, tail latency, and error budgets, as well as capacity and cost management for shared infrastructure.
Experience designing multi-tenancy, including quotas, isolation, chargeback/showback, and self-service provisioning APIs or CRDs.
Experience with container networking (CNI) and/or service mesh, and with workload identity, mTLS, and secrets management for data services.
Experience with managed Kubernetes (EKS/AKS/GKE), managed data services (RDS/Aurora, Cloud SQL, MSK, ElastiCache), and infrastructure-as-code tools such as Terraform or Crossplane.

Responsibilities

Lead the design and delivery of shared, multi-tenant managed Postgres, queueing/streaming, and key-value/cache services running on Kubernetes across a global fleet.
Own platform services from design through production operation, including their availability, resilience, and operating model.
Lead major team initiatives, translating ambiguous problems into executable designs with explicit availability, durability, and cost targets.
Define high-availability, failover, disaster-recovery, and multi-region architectures for owned services.
Build Kubernetes-native automation, including operators, controllers, CRDs, and self-service APIs, to provision, scale, upgrade, and fail services over without human intervention.
Partner with principal and distinguished engineers to align work with broader platform architecture and standards.
Partner with product teams to define service consumption contracts, tenancy models, and SLOs.
Identify and resolve technical risks, focusing on reliability, scalability, and operability; lead failure-mode analysis, game days, and post-incident reviews for stateful systems.
Design, code, and review core systems such as operators, controllers, infrastructure automation, and platform services.
Mentor mid-level and junior engineers through code reviews, design feedback, and pairing, raising engineering quality in distributed-systems and data-service design.